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UID:submissions.supercomputing.org_SC24_sess533_post180@linklings.com
SUMMARY:Fault Tolerance in Krylov Subspace Methods
DESCRIPTION:Sandesh Pandit (University of Alabama in Huntsville)\n\nToday’
 s complex HPC systems are incredibly powerful yet equally likely to experi
 ence failures. The scientific applications on these HPC systems are mostly
  iterative in nature. Iterative solvers have some inherent fault tolerance
 , but they are still susceptible to errors. One subset of these iterative 
 methods are the Krylov Subspace Methods. There has been limited research o
 n the fault tolerance of these methods against soft errors. We know Precon
 ditioned Conjugate Gradient (PCG) to be self-correcting in nature. But we 
 don’t know much about other methods in the Krylov Subspace. Our goal is to
  study the error propagation caused by Sparse Matrix-Vector Multiplication
  (SpMV) operation in Lanczos Method, Bi-Conjugate Gradient (BiCG) Method a
 nd PCG Method. By using the results from the experiments and knowledge fro
 m previous works, we will generalize our findings for all the Krylov Subsp
 ace Methods.\n\nRegistration Category: Tech Program Reg Pass, Exhibits Reg
  Pass\n\nSession Chairs: Ayesha Afzal (Friedrich-Alexander University, Erl
 angen-Nuremberg; Erlangen National High Performance Computing Center); Sal
 ly Ellingson (University of Kentucky); and Alan Sussman (University of Mar
 yland)\n\n
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